Vetted Engineering Professionals in California

“At HPE, led and deployed an enterprise-grade LLM document intelligence platform for an insurance client, automating extraction from highly variable PDFs/scans/emails and raising field accuracy from 74% to 93%. Built a LangChain/Pinecone/OpenSearch RAG framework to cut hallucinations by 37% and operationalized LangSmith evals in CI, driving a 41% triage accuracy lift and >33% fewer incorrect resolutions while partnering closely with claims operations via HITL workflows.”

“Backend/AI workflow engineer with experience at AirKitchenz, Uber, and Vivma Software, building production systems on AWS (Lambda, DynamoDB, Step Functions). Has a track record of major performance wins (DynamoDB latency 2s to <150ms; Postgres query 2s to ~180ms) and shipping LLM-powered onboarding and ticket-routing workflows with strong guardrails (schema validation, confidence thresholds, human-in-the-loop escalation).”

Joshua Hewitt

Screened

Senior Software Engineer specializing in Generative AI product development

San Francisco, USA9y exp

“AI product builder at Padlet who shipped multiple production LLM features for education workflows, including an AI document generator (AI Recipes) and a RAG-enabled in-product chat assistant. Built an AI microservice layer (LangChain) to swap model providers easily and created automated + human-in-the-loop evaluation systems (including ~100-test runs) to iterate on prompts and quality.”

Jianbo Wu

Screened

Mid-level AI/ML Engineer specializing in LLM reasoning and inference optimization

Santa Clara, CA4y exp

“Former Field Application Engineer at TestTorrent supporting proprietary hardware deployments. Built and integrated customer-requested benchmarking (including MLPerf-style work) by adapting GPU benchmark implementations and validating performance against NVIDIA baselines, plus delivered a backend fix that enabled customer performance testing and helped close a deal. Also has experience running models on AWS/GCP with multi-instance cost optimization techniques like memory offloading.”

Sri Lalitha

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices and FinTech

California, USA6y exp

“Backend engineer who owned a Python task management API with JWT auth, async notifications, and performance work (DB optimization/caching) to handle high volumes. Led an on-prem to Azure private cloud migration at Morgan Stanley using GitOps and IaC (Terraform/ARM) with phased rollout and rollback planning. Also built a Kafka real-time streaming pipeline with exactly-once/idempotent consumers and Prometheus/Grafana monitoring.”

Utkarsh Chandel

Screened

Senior Security Engineer specializing in detection engineering, cloud security, and DFIR

San Francisco, CA8y exp

“LLM workflow/agentic systems practitioner who has helped customers harden an LLM-based incident triage prototype into a trusted daily-use production system by adding observability, audits, confidence gating, and deterministic fallbacks. Brings an SRE-style approach to real-time debugging (trace replay, rollback/canary, safe toggles) and is experienced running developer-centric demos/workshops and partnering with sales on technical qualification and security/architecture artifacts.”

Kavya Aitagoni

Screened

Junior Full-Stack Engineer specializing in web platforms and live events

San Francisco, CA2y exp

“Full-stack product engineer with experience shipping user-facing web products end-to-end, including an event analytics dashboard and checkout improvements at Eventbrite. Stands out for combining frontend polish, backend reliability, and production-minded practices like idempotent APIs, query optimization, CI/CD, logging, and monitoring to improve conversion and reduce engineering dependency.”

“Built production AI systems in high-stakes domains, including a medical RAG chatbot focused on reducing hallucinations and a document-processing workflow that automated manual PDF extraction. Demonstrates strong end-to-end ownership across backend services, APIs, LLM integration, and iterative reliability improvements based on real usage and failure analysis.”

“Robotics software developer with hands-on ROS experience building a timer-driven closed-loop controller for a differential-drive robot in Gazebo, including square/figure-8 trajectory planning and RViz/rqt_graph-based debugging. Currently extending the system with LiDAR-based obstacle detection, safety overrides, and reactive velocity arbitration for collision-free motion.”

“Operations/project leader with hands-on experience driving an end-to-end transition of legacy customers from on-prem to cloud, including customer communication, structured execution planning, and operational handover. Also improved field operations productivity by selecting and implementing a field management tool that automated work orders and replaced spreadsheet/email workflows with mobile app-driven data flows.”

“Small-team builder of Promethium’s “Mantra” next-gen agentic text-to-SQL engine, using vector DB + LangGraph tooling and SQL validation/evaluation to improve query accuracy. Experienced in diagnosing production LLM workflow failures via LangSmith traces and in running hands-on developer workshops and pre-sales POCs with live debugging and real customer data.”

“Software engineer with hands-on AWS operations experience who owned an end-to-end manufacturing image ingestion pipeline (on-prem to AWS S3) integrated with MES/WMS. In an early-stage SaaS internship, diagnosed a load bottleneck using K6/New Relic and shipped an NGINX least-connection load-balancing solution that scaled to ~4000 RPS while reducing latency. Also improved maintainability and performance in a React/Node e-commerce codebase, cutting page load time from ~10s to 2.8s.”

Dallas Grimm

Screened

Mid-level QA Tester specializing in video game testing and bug management

Woodland Hills, CA4y exp

“Game designer with shipped experience on MLB The Show 20 (Road to the Show mode) and Call of Duty: Modern Warfare II (2019) campaign NVG feature, with a focus on progression tuning and realism/authenticity constraints. Currently building an Unreal Engine 5 game using Blueprints for level/VFX/interactions and C++ for scripting, iterating on exploration features like entering buildings.”

Qichen Zhao

Screened

Intern Software Engineer specializing in Applied AI and LLM systems

Los Angeles, CA0y exp

“Built and deployed a production RAG-based conversational "Yelp for AI tools" at Search-AI Inc., focused on personalized, explainable AI tool recommendations from thousands of options. Emphasizes production-grade reliability and performance (hybrid retrieval, async two-stage pipelines) and is also building a multi-agent orchestration layer (MAgIc) with typed memory and controlled coordination policies.”

Matthew Eis

Screened

Mid-level QA Tester specializing in video game testing and localization

Los Angeles, CA4y exp

“Game QA professional with live production experience at Nexon America owning localization verification for new MapleStory questlines (quests, VO, subtitles) and managing issues through Jira-based regression. Previously identified and documented a hard-to-repro main-quest progression blocker on Horizon Zero Dawn: Forbidden West, providing video-backed repro steps that enabled a fix before the next build shipped.”

“Frontend-leaning full-stack engineer who built and fully owned a production crew scheduling system at Archer using Next.js App Router/TypeScript, including a real-time, virtualized timeline handling ~1,200 crew over a 30-day window. Drove major post-launch improvements (60 FPS scrolling, PubNub-based soft-locking to cut conflicts ~90%) and created a correlation-ID-driven state replay/logging tool to debug hard-to-reproduce production issues while also contributing to FastAPI/SQLAlchemy/Postgres performance work.”

“Built and owns the full ProteinMenus AI pipeline end-to-end, spanning the iOS client, FastAPI backend, Gemini integration, Firestore, and Cloud Run deployment. Strongest signal is full-stack product ownership in an AI-driven consumer workflow, including monetization logic via an atomic credit system and architecture choices optimized for fast iteration after launch.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in backend systems and real-time analytics

California, USA5y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

“Full-stack developer who uses AI thoughtfully as a productivity multiplier rather than a substitute for engineering judgment. Built a stock search platform with React, Node.js, and MongoDB, and has experimented with multi-agent workflows across frontend, backend, debugging, and documentation while keeping rigorous human review over logic, testing, and maintainability.”

“Robotics software engineer with semiconductor wafer-handling automation experience at Mattson Technology, building C++ control software for ATM and vacuum robots coordinating through a load-lock (pressure/door/pump sequencing). Implemented multi-vendor communications with auto-detection across SECS serial and TCP/IP, and validated behavior using simulation + GUI animation, logging/sniffers, and hardware-in-the-loop testing; currently self-studying ROS 2.”

“Backend engineer who built an async FastAPI data pipeline at GHN Career Academy to replace a manual Excel-based workflow, migrating 30k+ contact records into Airtable with validation/deduplication and best-effort GPT-based enrichment. Emphasizes reliability under messy real-world data and partial failures via structured logging, retries, and resumable processing, unlocking downstream automations (e.g., Zapier and chatbots).”

“Backend/platform engineer who owned a real-time customer analytics microservice stack in Python/FastAPI with Kafka streaming into PostgreSQL, including schema enforcement (Avro) and high-throughput optimizations. Strong Kubernetes + GitOps practitioner (EKS/GKE, Helm, Argo CD) who has handled CI/CD reliability issues with automated pre-deploy checks and rollbacks, and supported major migrations (on-prem to AWS; VM to EKS) with blue-green cutover planning.”

“Backend engineer with hands-on manufacturing/production-systems experience at Wallbox, improving the Supernova charger rework process by streamlining part-number/component updates. Strong in building modular Python/Flask services with clean integration layers (Cosmos DB, NetSuite, traceability/label printing), plus deep SQLAlchemy/Postgres performance tuning. Also brings scalable AI/ML integration and deployment experience (OpenAI/Hugging Face/TensorFlow Serving, Docker/FastAPI/Nginx) and multi-tenant schema isolation with RBAC.”